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. 2006:2006:244-8.

Infodemiology: tracking flu-related searches on the web for syndromic surveillance

Affiliations

Infodemiology: tracking flu-related searches on the web for syndromic surveillance

Gunther Eysenbach. AMIA Annu Symp Proc. 2006.

Abstract

Background: Syndromic surveillance uses health-related data that precede diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health response.

Objective: While most syndromic surveillance systems rely on data from clinical encounters with health professionals, I started to explore in 2004 whether analysis of trends in Internet searches can be useful to predict outbreaks such as influenza epidemics and prospectively gathered data on Internet search trends for this purpose.

Results: There is an excellent correlation between the number of clicks on a keyword-triggered link in Google with epidemiological data from the flu season 2004/2005 in Canada (Pearson correlation coefficient of current week clicks with the following week influenza cases r=.91). The "Google ad sentinel method" proved to be more timely, more accurate and - with a total cost of Can$365.64 for the entire flu-season - considerably cheaper than the traditional method of reports on influenza-like illnesses observed in clinics by sentinel physicians.

Conclusion: Systematically collecting and analyzing health information demand data from the Internet has considerable potential to be used for syndromic surveillance. Tracking web searches on the Internet has the potential to predict population-based events relevant for public health purposes, such as real outbreaks, but may also be confounded by "epidemics of fear". Data from such "infodemiology studies" should also include longitudinal data on health information supply.

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Figures

Figure 1
Figure 1
Normalized data from Fluwatch (influenza cases, lab tests, ILI reports from sentinel physicians) and Google (number of clicks on an keyword-triggered influenza link).
Figure 2
Figure 2
Scatter plot (with regression line) showing the excellent correlation between “clicks” and flu cases in the following week (*)
Figure 3
Figure 3
Scatter plot (with regression line) showing the considerably worse correlation between sentinel physicians’ ILI reports and flu cases in the following week (**)

References

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    1. Mandl KD, Overhage JM, Wagner MM, Lober WB, Sebastiani P, Mostashari F, et al. Implementing syndromic surveillance: a practical guide informed by the early experience. J Am Med Inform Assoc. 2004;11:141–50. - PMC - PubMed

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